When tools are used in a manufacturing or service environment, it is important that tools be returned to a storage unit, such as a tool box, after use. Employers typically perform a manual inventory check of the tool box to minimize or eliminate the problem of misplacement or theft of expensive tools. Companies can conduct random audits of employee's toolbox to prevent theft and monitor tool location.
Some industries have high standards for inventory control of tools, for preventing incidents of leaving tools in the workplace environment where they could cause severe damages. For the aerospace industry, it is important to ensure that no tools are accidentally left behind in an aircraft or missile being manufactured, assembled or repaired. The Aerospace Industries Association even establishes a standard called National Aerospace Standard including recommended procedures, personnel management and operations to reduce foreign object damage (FOD) to aerospace products. FOD is defined as any object not structurally part of the aircraft. The most common foreign objects found are nuts, bolts, safety wire, and hand tools. Inventory control over tools is critical to prevent tools from being left in an aircraft.
Some toolboxes includes build-in inventory determination features to track inventory conditions of tools stored in those toolboxes. For example, some toolboxes dispose contact sensors, magnetic sensors or infrared sensors in or next to each tool storage locations, to detect whether a tool is placed in each tool storage location. Based on signals generated by the sensors, the toolboxes are able to determine whether any tools are missing. While this type of inventory check may be useful to some extents, it suffers from various drawbacks. For instance, if a sensor detects that something is occupying a storage location, the toolbox will determine that no tool is missing from that storage location. However, the toolbox does not know whether the right kind of tool is indeed placed back in the toolbox or it is just some objects placed in the storage location to cheat the system. Furthermore, disposing sensors for numerous storage locations in a toolbox is tedious and costly, and the large number of sensors is prone to damages or malfunctions which will produce false negative or positive alarms.
Accordingly, there is a need for an effective inventory control system that that could assist tracking and accounting for usage of tools and whether they are properly put back after usage. There is also a need for an inventory control system which knows exactly what tool is removed or returned to a tool box. Furthermore, as multiple workers may have access to the same tool box, there is another need for an inventory control system that can track a user and his or her usage of tools, to determine responsibilities for any tool loss or misplacement.
This disclosure describes various embodiments of highly automated inventory control systems that utilize unique machine imaging and methodology for identifying an inventory condition in the storage unit. Illustrative features include the ability to process complex image data with efficient utilization of system resources, autonomous image and camera calibrations, identification of characteristics of tools from image data, adaptive timing for capturing inventory images, efficient generation of reference data for checking inventory status, autonomous compensation of image quality, etc.
According to one aspect of this disclosure, systems and methods with novel image calibration are proposed. An exemplary inventory control system includes at least one storage drawer, each storage drawer including a plurality of storage locations for storing objects, wherein each drawer is associated with an identifier with known color attributes; a data storage system storing, for each storage drawer, information of the known color attributes of the associated identifier; and a data processor configured to: access data of a captured image of one of the storage drawers along with the associated identifier; access information of the known color attributes of the identifier associated with the drawer corresponding to the captured image; determine color attributes of the identifier in the captured image; determine a corrector factor (make change to claim), such as an offset value, based on the color attributes of the identifier in the captured image and the known color attributes of the identifier; and apply the correction factor to subsequent images captured by the image sensing device. A captured image of a drawer may be an image of the entire drawer, or a partial image of the drawer.
According to another embodiment, an exemplary comprises at least one storage drawer, each storage drawer including a plurality of storage locations for storing objects, wherein each drawer is associated with at least two known and non-repeating reference patterns; an image sensing device configured to capture a partial image of one of the storage drawers along with the associated reference patterns, wherein the reference patterns are provided in such a manner that the at lest two known and non-repeating reference patterns are in every image taken by the image sensing device; a data storage system storing, for each storage drawer, location information of the reference patterns in each drawer; and a data processor. The data processor is configured to access image data of the partial image of the drawer captured by the image sensing device; extract information related to the reference patterns in the partial image of the drawer; access the location information stored in the data storage system; and determine a portion of the drawer to which the partial image corresponds based on the reference patterns in the partial image and the location information.
The image sensing device may be configured to capture multiple partial images of the drawer, and the data processor may determine, for each of the multiple partial images taken by the image sensing device, a portion of the drawer to which each of the multiple partial images corresponds based on the reference patterns in each partial image and the location information stored in the data storage system. The multiple partial images may be stitched together to form a larger image of the drawer.
According to another embodiment, an exemplary inventory control system comprises at least one storage drawer, each storage drawer including a plurality of storage locations for storing objects, wherein each drawer is associated with at least two known and non-repeating reference patterns; an image sensing device configured to capture partial images of a storage drawer along with the associated reference patterns, wherein the reference patterns are provided in such a manner that the at lest two known and non-repeating reference patterns are in every image taken by the image sensing device; a data storage system storing, for each storage drawer, location information of the reference patterns in each drawer; and a data processor. The data processor is configured to access image data of a first partial image and a second partial image of the drawer captured by the image sensing device; extract information related to the reference patterns in the first partial image and the second partial image; access the location information stored in the data storage system; determine portions of the drawer to which the first partial image and the second partial image correspond based on the reference patterns in the first and second partial images and the location information; and determine a moving speed of the drawer based on the portions of the drawer to which the first partial image and the second partial image correspond, and a time difference between the first partial image and the second partial image. In one aspect, the data processor determines an imaging frequency according to the moving speed, the image sensing device captures images of the drawer base on determined imaging frequency.
According to still another embodiment, an inventory control system comprises at least one storage drawer, each storage drawer including a plurality of storage locations for storing objects, wherein each drawer is associated with at least two known and non-repeating reference patterns; an image sensing device configured to capture at least a partial image of a storage drawer along with the associated reference patterns, wherein the reference patterns are provided in such a manner that the at lest two known and non-repeating reference patterns are in every image taken by the image sensing device; a data storage system storing, for each storage drawer, location information of the reference patterns in each drawer; and a data processor. The data processor is configured to: access image data of the partial image of the drawer captured by the image sensing device; extract information related to the reference patterns in the partial image; access the location information stored in the data storage system; determine a portion of the drawer to which the partial image corresponds based on the reference patterns in the first and second partial images and the location information; determine a needed adjustment to the captured image based on a difference between the partial image of the drawer and characteristics of the determined portion of the drawer; and apply the needed adjustment to the captured image. The determined adjustment may be applied to subsequent images taken by the image sensing device.
According to yet another embodiment, an inventory control system comprises at least one storage drawer, each storage drawer including a plurality of storage locations for storing objects; an image sensing device configured to capture an image of a target including known reference patterns, wherein relative spatial relationships of the reference patterns are known; a data storage system storing information of the known spatial relationships of the reference patterns; and a data processor. The data processor is configured to access image data of the image of target captured by the image sensing device; extract information related to the reference patterns in the captured image; access the information of the known spatial relationships of the reference patterns stored in the data storage system; determine a difference between the reference patterns in the captured image and the known spatial relationships of the reference patterns; determine a needed adjustment to the captured image based on the difference; and apply the needed adjustment to subsequent images captured by the image sensing device. Systems and methods described herein may be implemented using one or more computer systems and/or appropriate software.
It is understood that embodiments, steps and/or features described herein can be performed, utilized, implemented and/or practiced either individually or in combination with one or more other steps, embodiments and/or features.
Additional advantages and novel features of the present disclosure will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following, or may be learned by practice of the present disclosure. The embodiments shown and described provide an illustration of the best mode contemplated for carrying out the present disclosure. The disclosure is capable of modifications in various obvious respects, all without departing from the spirit and scope thereof. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive. The advantages of the present disclosure may be realized and attained by means of the instrumentalities and combinations particularly pointed out in the appended claims.